R Notebook

Import Dataset and create working dataset:

#install.packages("plotly")
library(plotly)

package 㤼㸱plotly㤼㸲 was built under R version 4.0.4Registered S3 method overwritten by 'data.table':
  method           from
  print.data.table     
Registered S3 method overwritten by 'htmlwidgets':
  method           from         
  print.htmlwidget tools:rstudio

Attaching package: 㤼㸱plotly㤼㸲

The following object is masked from 㤼㸱package:ggplot2㤼㸲:

    last_plot

The following object is masked from 㤼㸱package:stats㤼㸲:

    filter

The following object is masked from 㤼㸱package:graphics㤼㸲:

    layout

game_melt %>% 
    group_by(Region,Year,Genre) %>%
    summarise(net = sum(`Copies Sold`))

`summarise()` regrouping output by 'Region', 'Year' (override with `.groups` argument)

Graph time baby!

#Number of Copies Sold
library(tidyverse)
graph1 <- game_melt %>% 
    filter(Region == "NA_Sales") %>%
    group_by(Region,Year,Genre) %>%
    summarise("Copies Sold" = sum(`Copies Sold`)) %>% 
    ggplot() +
    aes(x=Year,
        y=`Copies Sold`,
        fill = Genre) + 
    geom_bar(stat="identity")+
    theme(axis.text.x = element_text(angle = 90, hjust=0.95, vjust=0.2))+
    ylab("Number of Copies Sold (in millions)")

`summarise()` regrouping output by 'Region', 'Year' (override with `.groups` argument)

ggplotly(graph1)

#Number of Copies Sold
library(tidyverse)
graph2 <- game_melt %>% 
    filter(Region == "NA_Sales") %>%
    group_by(Region,Year,Genre) %>%
    count(Year,Genre) %>%
    rename(`Number of Releases`="n")%>% 
    ggplot() +
    aes(x=Year,
        y=`Number of Releases`,
        fill = Genre) + 
    geom_bar(stat="identity")+
    theme(axis.text.x = element_text(angle = 90, hjust=0.95, vjust=0.2))+
    ylab("Number of games released")
ggplotly(graph2)

#Number of Platforms, Genres and Publishers with games > 100 copies sold 
graph3 <- game_melt %>% 
    filter(Region == "JP_Sales") %>%
    group_by(Year)%>%
    melt(id.vars=c("Year"),measure.vars=c("Genre","Platform","Publisher")) %>%
    rename(Category='variable') %>% 
    group_by(Year,Category) %>%
    unique() %>%
    count(Year,Category) %>%
    rename(`Counts of Genres, Publishers and Platforms`= n) %>% 
    ggplot() +
    aes(x=Year,
        y=`Counts of Genres, Publishers and Platforms`,
        fill = Category) + 
    geom_bar(stat="identity")+
    theme(axis.text.x = element_text(angle = 90, hjust=0.95, vjust=0.2))+
    ylab("Counts of Genres, Publishers and Platforms")
ggplotly(graph3)